... sequence information. Using the data filtered by the band-pass filter, graph neural networks with distance-awareness and sequence-awareness are applied to capture high-order spatial-temporal connections within diverse graph topologies. The model leverages contrastive learning for self-supervised...

... usually ignore the problem that the drift of user interests may lead to the generation of new features when they compute feature interactions. Based on this, this paper aims to design a model to address this issue. Design/methodology/approach First, the authors use graph neural networks to model users...